Artificial intelligence and machine learning in cardiotocography: A scoping review.

Journal: European journal of obstetrics, gynecology, and reproductive biology
Published Date: Dec 9, 2022

Abstract

INTRODUCTION: Artificial intelligence (AI) is gaining more interest in the field of medicine due to its capacity to learn patterns directly from data. This becomes interesting for the field of cardiotocography (CTG) interpretation, since it promises to remove existing biases and improve the well-known issues of inter- and intra-observer variability.

Authors

  • Jasmin L Aeberhard
    Medical Faculty of the University of Bern, Switzerland. Electronic address: jasmin-aeberhard@bluewin.ch.
  • Anda-Petronela Radan
    Department of Obstetrics and Feto-maternal Medicine, University Hospital of Bern, Switzerland.
  • Ricard Delgado-Gonzalo
    Centre Suisse d'Électronique et de Microtechnique CSEM, Neuchâtel, Switzerland.
  • Karin Maya Strahm
    Department of Obstetrics and Feto-maternal Medicine, University Hospital of Bern, Switzerland.
  • Halla Bjorg Sigurthorsdottir
    Centre Suisse d'Électronique et de Microtechnique CSEM, Neuchâtel, Switzerland.
  • Sophie Schneider
    Department of Obstetrics and Feto-maternal Medicine, University Hospital of Bern, Switzerland.
  • Daniel Surbek
    Department of Obstetrics and Feto-maternal Medicine, University Hospital of Bern, Switzerland.

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